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Effect of operating parameters on the separation of proteins in aqueous solutions by dead-end ultrafiltration
Desalination 234 (2008) 116–125
Effect of operating parameters on the separation of proteins in aqueous solutions by dead-end ultrafiltration Su-Hsia Lina*, Chia-Lin Hungb, Ruey-Shin Juangb a
Department of Chemical Engineering, Nanya Institute of Technology, Chung-Li 320, Taiwan Fax þ886-3-4361070; email: [email protected] b Department of Chemical Engineering and Materials Science, Yuan Ze University, Chung-Li 32003, Taiwan Received 27 June 2007; accepted revised 21 September 2007
Abstract Ultrafiltration (UF) separation of hemoglobin (Hb, pI 7.1, MW 68,000) and bovine serum albumin (BSA, pI 4.7, MW 67,000) in aqueous solutions with PES (polyethersulfone, MWCO ¼ 100 kDa) and PAN (polyacrylonitrile, MWCO ¼ 100 kDa) membranes was studied. Experiments were performed by changing operating parameters including solution pH (4–7.5), initial protein concentration (100–500 ppm), transmembrane pressure (TMP, 10–50 psi), ionic strength (0.01–0.1 M), and stirring speed (100–300 rpm). More effective separation was achieved at a lower protein concentration, a lower TMP, or a pH above the pI of Hb with PAN membrane. Under the conditions of low pressure, low protein concentration, and low ionic strength, the interactions between the charges of proteins and membranes were important. The flux decreased more sharply when pH was lower than 7.1. Response surface methodology by the Box-Behnken model was used to examine the role of each process variable on protein rejection and UF flux. A second-order polynomial regression model could properly interpret the experimental data with an R2 value of 0.97, based on the estimated rejection of BSA up to 99.7%. Interactions between these operating parameters and the significance effects on UF operation were also discussed. Keywords: Separation; Proteins; Dead-end ultrafiltration; Operating parameters; Flux decline
1. Introduction The separation or purification of proteins is a crucial process in biotechnology due to its wide range of applications in biomedical and food
*Corresponding author.
industries. The techniques used for protein separation and purification such as chromatography, electrophoresis, and affinity operations have been recently established for producing small quantities of proteins in research laboratories. However, these techniques are rather difficult to scale-up, which limits production
Presented at the Fourth Conference of Aseanian Membrane Society (AMS 4), 16–18 August 2007, Taipei, Taiwan. 0011-9164/08/$– See front matter # 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.desal.2007.09.077
S.H. Lin et al. / Desalination 234 (2008) 116–125
levels [1–2]. Besides, some methods like chromatography and electrophoresis require complex instrumentation support to run efficiently, and usually yield low throughput of the products at an extremely high process cost. Hence, the separation techniques that can yield high throughput of the products at a low cost are highly desired in biotechnological industries. Of these potential candidates, ultrafiltration (UF) has attracted a considerable amount of attention in recent years for the separation of proteins due to comparatively gentler towards the proteins than separation process on phase changes and more economical than gel chromatography [3–8]. The applications of UF are limited to systems where the solutes to be separated have more than 10-fold difference in molecular weight (MW). Molecular size becomes the sole criteria for separation purposes in such cases. However, it is possible to separate solutes having comparable MWs by adequately manipulating the parameters such as pH, ionic strength, and transmembrane pressure (TMP) [3]. van Eijndhoven et al. [4] have shown the possibility to improve the selectivity of albumin (BSA)/hemoglobin (Hb) by reducing salt concentration and adjusting the pH to near isoelectric point (pI) of Hb. Feins and Sirkar [5] have separated binary proteins with relatively close in MW using internally staged UF. The fractionation of lysozyme (Ly)/ovalbumin and Ly/myoglobin mixtures by 100-kDa hydrophilic polyacrylonitrile membrane has been studied in a vortex flow ultrafilter [9]. Saksena and Zydney [3] have also studied the transport of IgG and BSA using 100- and 300-kDa PS membranes in a stirred cell. The separation of Ly and BSA by Amicon PM 30 membrane and the effect of salt concentration and BSA-Ly interaction on the rate of Ly washout were also examined [10]. However, the main problem restricting practical applications is membrane fouling and the resulting time-dependent flux and rejection behavior. The main factors that affect membrane fouling
117
are the physicochemical properties of feed and membrane [9]. This study will focus on these two factors. In this work, Hb and BSA were chosen as model proteins and the membranes with a molecular-weight cut-off (MWCO) of 100 kDa were selected. The effects of ionic strength, stirring speed, solution pH, and membrane hydrophobility were investigated in order to improve the separation and the performance of UF process. Response surface methodology by the Box-Behnken model was used to examine the role of each process variable on protein rejection and UF flux. A second-order polynomial regression model could use to predict the experimental data. Interactions between these process parameters and the significance effects on UF operation were also discussed. 2. Response surface methodology In the factorial design of experiments, when responses and input variable factors (e.g., the initial protein concentration, TMP, stirred speed, and solution pH) are continuous, it is very useful to consider the factor response relationship in terms of a mathematical model such as the response function. For qualitative factors where there is no continuous link between the response and the levels of a factor, it is necessary to consider a comparison of the response between two levels of a qualitative factor. The factorial approach results in a considerable saving of time and materials devoted to the experiments. First, the factor that is independent of all simple effects of a factor is equal to its main effect. The consequences of variations in the factors and the main effects are the only quantities that need to be stated. Second, each main effect in factorial experiments is estimated with the same accuracy as if the whole experiment had been devoted to the factor alone [11]. Thus, the advantages of this methodology contain (i) all experimental units are used in evaluating effects, resulting
S.H. Lin et al. / Desalination 234 (2008) 116–125
in the most efficient use of resources, (ii) the effects are evaluated over a wider range of conditions with the minimum of resources, and (iii) a factorial set of treatments is optimized for estimating main effects and interactions. In this work, the factorial design experiments are used in the analysis of protein rejection. Four input variables, protein concentration, TMP, stirred speed and solution pH, are considered. The use of variance analysis and factorial design of experiments allows us to express the rejection of protein as a polynomial model. If the levels of the factors are equally spaced, the orthogonal polynomial adopted to give a more detailed equation for the response will be [12] Y ¼ b0 þ b1 C þ b2 R þ b3 H þ b4 P þ b11 C 2 þ b22 R2 þ b33 H 2 þ b44 P2 þ b12 CR þ b13 CH þ b14 CP þ b23 RH þ b24 RP þ b34 HP
ð1Þ
where Y is the predicted response (rejection of protein), bi’s are the coefficients of the polynomial equation, C is the initial protein concentration (ppm), R is the stirring speed (rpm), H is the solution pH, and P is the TMP (psi). The method used for evaluating the effects and their sums squares is a simple extension of the method introduced by Yates for a 200 factorial design [11]. It is assumed that the main and interaction effects are all linear combinations of the observations. This design is preferred because relatively few combinations of the variables are adequate to estimate potentially complex response function. The total 29 experiments are needed to calculate 15 coefficients of the second-order polynomial regression model. This model contains 1 block term, 4 linear terms, 4 quadratic terms, and 6 interaction terms. A convenient way of estimating these effects for a factorial design is to establish a table of appropriate multipliers that applied to the observations.
3. Experimental 3.1. Reagents and membranes Hemoglobin (Hb, MW 68,000) and bovine serum albumin (BSA, MW 66,430) were offered from Sigma Co. The pI values for Hb and BSA are 7.1 and 4.9, respectively. The zeta potential of proteins was shown in Fig. 1. The single protein solution was prepared by dissolving protein in 50 mM phosphate buffer, in which the solution pH was controlled in the range 4.0–7.5. The solution was gently agitated for 1 h to ensure homogeneity at 25 C. Prior to use, the phosphate buffer was filtered through a 0.45-mm Durapore membrane (Millipore, Bedford, MA). The binary protein solution was obtained by mixing single stock solutions with gentle agitation for 20 min, and the solution was also pre-filtered through a 0.45-mm Durapore membrane to remove undissolved proteins and large particulates. The ionic strength of protein solutions was adjusted by the addition of NaCl. Polyestersulfone (PES) and polyacrylonitrile (PAN) disc membranes used were supplied from Osmonics Co. Both asymmetric membranes had a molecular-weight cut-off (MWCO) of 100 kDa. Prior to use, these membranes were 60 40
Zeta potential (mV)
118
BSA HB
20 0 –20 –40 –60
2
3
4
5
6
7
8
9
10
pH
Fig. 1. Zeta potentials of BSA and HB proteins at various pH values.
S.H. Lin et al. / Desalination 234 (2008) 116–125
The average permeate flux (J) at each run was calculated in the time intervals t1 and t2 by
–10 –12
Zeta potential (mV)
119
–14
J¼
–16
ð V2 V1 Þ Aðt2 t1 Þ
ð2Þ
–18 –20 PES membrane PAN membrane
–24 –22
3
4
5
6
7
8
9
10
where A is the effective membrane area cm2) and V is the volume of the permeate (cm3). Also, the average rejection of each protein (R) was obtained as follows:
pH
Fig. 2. Zeta potentials of PES and PAN membrane at various pH values.
soaked overnight in protein solutions to ensure the attainment of equilibrium between the membrane and protein molecules. Fig. 2 shows the zeta potentials of fresh membranes. The method was described in our previous study [13]. They are negatively charged under the pH range studied.
3.2. Dead-end UF experiments Batch UF experiments were performed in a stirred glass cell of 8.0 cm I.D. and 8 cm height (Amicon Model 8400). It had an effective membrane area of 41.8 cm2 and a cell volume of 400 cm3. The applied pressure of stirred cell was controlled by nitrogen gas. The feed (working) volume of solution was 250 cm3 and the stirring speed was in the range 100–300 rpm. The highest speed of 300 rpm was selected because it could provide effective agitation but prevent the formation of a series vortex in the cell. Experiments were carried out at 25 C. The solution pH was measured using a pH meter (Horiba F-23, Japan). Except in continuous experiments, the permeate was collected in every increment of 20 cm3.
R¼1
Cp Cf
ð3Þ
where Cp and Cf are the protein concentrations in the permeate and feed, respectively. The concentrations of binary proteins in the samples were determined using HPLC (Hitachi L-7100) on a Hypersil WP300 column (particle size 5 mm). Two mixtures of 0.1 vol.% trifluoroacetic acid in water and 0.1 vol.% trifluoroacetic acid in propanol were used as the mobile-phase gradient. The flow rate was 1 cm3/min. An aliquot of 10 mL of the sample was injected and analyzed with an UV detector (L-7420) at a wavelength of 280 nm. Each experiment was at least duplicated under identical conditions. The reproducibility of the measurements was within 7% (mostly, 5%).
3.3. Cleaning operations After the completion of each experiment, the membrane used was cleaned in ultrasonic cleaner with 0.1 M NaOH for approximately 30 min once and then with deionized water twice. The pure water flux was then re-checked. The integrity and performance of the membrane was considered to be maintained if pure water flux was within 95% of the virgin membrane. The cleaned membranes were stored in 0.05% sodium azide solution at 4 C.
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4. Result and discussions 4.1. Effects of TMP, initial concentration, and pH on the rejection of BSA Three levels of the initial protein concentration, solution pH, stirring speed, and TMP are selected for factorial design of experiments according to the method by Yates [11]. A total of 29 experiments were used for error estimation of the four-factorial linear and quadratic interactions. The main and interaction effects obtained are multiplied by appropriate coefficients and predicted data as shown in Table 1. Figs. 3–5 show the effects of TMP, initial protein concentration, and pH on the rejection of BSA with PAN membranes. It is found that the rejection of single protein (BSA) increases with increasing TMP and initial concentration (Fig. 1). At low TMP (10 psi), a maximum rejection of BSA is found at low pH, particular lower than pI value of the protein (4.9). This is because the positively charged protein would adsorb onto the negatively charged membrane at pH < 4.9. The result is consistent with previous reports
Fig. 3. Protein rejection on 3-D graphics for response surface optimization vs. concentration and applied pressure.
that the transmission of protein (BSA) decreases with increasing pH [14]. However, the influence of pH is negligible at high TMP and high initial concentration. In general, the linear terms are more significant than the quadratic interactions. It is shown
Table 1 Coefficients of the model [Eq. (1)] for rejection of BSA using the 100 kDa-PAN Coefficient
Value
Standard error
t for H0: coeff. ¼ 0
Prob > |t|
b0 b1 b2 b3 b4 b11 b22 b33 b44 b12 b13 b14 b23 b24 b34
1.605 1.37 –0.17 –1.31 2.04 –0.64 –0.52 0.96 –1.68 0.27 0.013 –0.14 –0.11 0.36 0.86
0.2362 0.1525 0.1525 0.1525 0.1525 0.2074 0.2074 0.2074 0.2074 0.2641 0.2641 0.2641 0.2641 0.2641 0.2641
– 8.98 –1.085 –8.573 13.37 –3.081 –2.4956 4.6088 –8.097 1.0235 0.049 –0.5356 –0.42178 1.3518 3.258
– <0.0001 0.2962 <0.0001 <0.0001 0.0081 0.0257 0.0004 <0.0001 0.3234 0.9613 0.6006 0.6796 0.1979 0.0057
S.H. Lin et al. / Desalination 234 (2008) 116–125
121
1.4
Flux (cm3/cm2 s)
1.2
pH 7.65 pH 7.10 pH 6.00 H2O
1.0
C0 = 100 ppm 300 rpm
0.8 0.6 0.4 0.2 0.0
0
10
20
30
40
50
60
ΔP (psi)
Fig. 4. Protein rejection on 3-D graphics for response surface optimization vs. solution pH and applied pressure.
that TMP and initial protein concentration are the most significant factors, and stirring speed is the less significant one in the present filtration process. This confirms the experimental observations as indicated above. It is noticed that the model parameters are determined by an ANOVA fitting exercise, so that the model could adequately describe most of the data. The model can then be used to ‘‘predict’’ the remaining data, e.g., the measurement made at 0.1 psi.
Fig. 6. Effect of pH and P on UF flux with PAN membranes (C0,BSA ¼ 100 ppm).
In other words, this model is essential predictive, rather than corrective.
4.2. Effects of pH and TMP on the flux of protein solutions Figs. 6 and 7 illustrate the effect of pH and TMP on the flux of binary proteins solution with PAN membranes. It is observed that the flux increases sharply with TMP and then levels off, particularly at lower initial protein concentrations (Fig. 6). Also, the effect of solution pH is 1.4 C0 = 500 ppm 300 rpm PAN pH 7.65 pH 7.10 pH 6.00 H2O
Flux (cm3/cm2 s)
1.2 1.0 0.8 0.6 0.4 0.2 0.0
0
10
20
30
40
50
60
ΔP (psi)
Fig. 5. Protein rejection on 3-D graphics for response surface optimization vs. concentration and solution pH.
Fig. 7. Effect of pH and P on UF flux with PAN membranes (C0,BSA ¼ 500 ppm).
S.H. Lin et al. / Desalination 234 (2008) 116–125
more important at low protein concentrations. At pH 6, the positively charged Hb would adsorb easily on the negatively charged membrane, and block the pores of the membrane. However, the repulsive force between the negatively charged proteins and membrane reduce the fouling at pH > 7.1. At higher protein concentration and TMP (Fig. 7), the effect of pH on the flux can be neglected. In such situations, the concentration polarization is more important, which is also indicated by the results of Design Expert mentioned above.
Figs. 8 and 9 show the effects of solution pH and TMP on the separation factor ( ), which is defined as ð1 RBSA Þ ð1 RHb Þ
ð4Þ
As shown in Fig. 8, the higher separation factor is obtained at lower TMP and at pH near the pI of Hb. This is because neutral Hb molecules (at pH 7.1) are easily aggregated themselves and not absorbed on the surface of the membrane by electrostatic attraction, resulting 4
β
3
pH 7.50 pH 7.10 pH 6.00
2
1
0
0
10
20
30
40
3
C BSA,0 = C Hb,0 = 500 ppm pH 7.50 pH 7.10 pH 6.00
2
1
0
0
10
20
30
40
50
60
ΔP (psi)
Fig. 9. Effect of pH and P on separation factor with PAN membranes (C0,BSA ¼ 500 ppm).
4.3. Effects of pH and TMP on the separation factor
¼
4
β
122
50
60
ΔP (psi)
Fig. 8. Effect of pH and P on separation factor with PAN membranes (C0,BSA ¼ 100 ppm).
in less fouling, but BSA can pass easily through the pores of the membrane. In contrast to pH 6.0, the serious fouling at pH 7.1 is found (Figs. 6 and 7). The positively charged Hb is preferentially absorbed on the surface of negatively charged membrane, so the separation of two proteins is difficult at pH 6.0. At pH 7.5, the separation factor is smaller than 1 (Fig. 8), which means that the amount of Hb passing through the membrane is more than that of BSA (that is, RHb < RBSA). This is a result of the greater repulsive force between BSA molecules and the membrane, compared to that between Hb molecules and the membrane. Some inconsistent results with earlier studies are actually observed. Watanabe et al. [15] have reported that relatively high levels of denaturation and consequently aggregation are found in acidic solution with pH below the pI of BSA. At such low pH, the forces between protein layers and polymeric films would increase. It was also shown that below isoelectric point the tertiary structure of proteins was disturbed upon interaction with the polymeric films [16]. At high feed concentration of 500 ppm, however, the electrostatic force can be ignored, and the serious fouling makes the separation factor close to 1 as shown in Fig. 9.
S.H. Lin et al. / Desalination 234 (2008) 116–125
4.4. Effects of protein concentration and ionic strength on the separation factor
0.5
10 C 0 (ppm) BSA:HB = 300:100 BSA:HB = 100:300 BSA:HB = 100:500 BSA:HB = 500:100
ΔP = 10 psi 300 rpm PAN
β
6
0.01 M 0.05 M 0.1 M
0.4
CBSA = CHB = 100 ppm ΔP = 10 psi 300 rpm PAN
0.3
β
At a concentration ratio (¼CHb,0/CBSA,0) of 1/3 or 1/5 (Fig. 10), BSA is likely the major protein deposited on the membrane. The dense deposition would retain both proteins passing through the membrane. However, at low values of 3 and 5, the separation factor closes 1 under the pH ranges studied. The neutral Hb is transported easier through the pores of the membrane by pressure driving force at pH 7.1, which leads to a low . But the separation factor is lower than 1 at pH > 7.1. The effect of ionic strength on the value is shown in Fig. 11. All the separation factor is smaller than 1, which decreases with increasing ionic strength at pH > 7.1. The addition of NaCl would offset the effect of electrostatic interactions, and decrease the thickness of double layer. The molecular size of Hb is seriously reduced, and it will pass through the membrane, resulting in a low of 0.025 at an ionic strength of 0.01 M and pH 7.5. This represents that another high separation factor (1/ ) is obtained. Although the molecular weight of Hb is higher that of BSA, the elliptical shape of Hb would pass easily through the pores of the membrane (equivalent
8
123
0.2
0.1
0.0 6.4
6.6
6.8
7.0
7.2
7.4
7.6
pH
Fig. 11. Effect of pH and ionic strength on separation factor with PAN membranes (C0,BSA ¼ 500 ppm).
radium in nm, BSA: 14 4 4, Hb: 7 5.5 5.5; and ellipsoidal diameter in nm: BSA: 3.61, Hb: 3.1 [17]). van Eijndhoven et al. [4] have ever investigated the selective separation of Hb and BSA with 100-kDa PES membrane in a stirred UF cell. They pointed out that a very high selectivity (1/ ¼ 70) is obtained for the separation of BAS and Hb at pH 7 and 0.0023 M NaCl. At the same ionic strength of 0.01 M, a higher separation factor with 100-kDa PAN membrane (1/ ¼ 40) is obtained here compared to that with 100-kDa PES membrane (1/ ¼ 5) in their experiments [4]. Causserand et al. [17] have also examined the separation of BSA and Hb by the addition of montmorillonite to enhance the selectivity with 0.1 mm PVDF membrane. However, the value increased from 1.61 to 5.63 only by adding 1.0 g/L at pH 7 and an ionic strength of 1 mM.
4 2
4.5. Effect of membrane materials on the flux and separation factor
0 6.4
6.6
6.8
7.0
7.2
7.4
7.6
pH
Fig. 10. Effect of pH and ionic strength on separation factor with PAN membranes (C0,BSA ¼ 500 ppm).
The effect of membrane materials on the flux is shown in Fig. 12. The lower flux is obtained with more hydrophobic membranes (PES). This is because that protein would adsorb easily on the
124
S.H. Lin et al. / Desalination 234 (2008) 116–125
1.2
pH 7.50, 100 ppm pH 7.10, 100 ppm pH 6.00, 100 ppm pH 7.50, 500 ppm pH 7.10, 500 ppm
(a)
1.0
J/J 0
0.8 PAN: 100 kDa Pressure: 10 psi Stirred rate: 300 rpm
0.6 0.4
PAN membrane is higher than that with PES membrane. It should be noted that a separation factor of 0.02 is obtained with PES membrane at pH 7.5 and an initial protein concentration of 100 ppm.
0.2 0.0
0
100
200
300
400
500
600
5. Conclusions
1.2 (b) 1.0
PES: 100 kDa pH: 7.50 Pressure: 10 psi Stirred rate: 300 rpm
J/J 0
0.8 0.6
CHb = CBSA 100 ppm 300 ppm 500 ppm
0.4 0.2 0.0
0
100
200
300
400
500
600
Time (s)
Fig. 12. Comparison of flux with PAN and PES (P ¼ 10 psi).
more hydrophobic membrane. These findings are similar to those reported by Musale and Kulkarni [18]. The separation factor at different solution pH with PES membrane is shown in Fig. 13. Comparing two kinds of membrane materials at an initial concentration of each protein of 100 ppm, we find that the separation factor with
The effects of operating parameters on the flux and separation factor in dead-end UF of binary BSA and Hb (with similar molecular weights) using PES and PAN membranes (MWCO, 100 kDa) were systematically investigated. The following results were obtained. (1) The UF flux and protein rejection were strongly affected by the applied pressure, solution pH and ionic strength, particularly mainly by the applied pressure and feed concentration. (2) The high separation of BSA and Hb can be obtained at the condition of lower applied pressure, low ionic strength and solution pH > pI of Hb. (3) Under comparable conditions, PAN membrane displayed higher UF flux and higher separation factor than that of PES membrane.
4 PES: 100 kDa ΔP : 10 psi Stirred rate: 300 rpm
3
Nomenclature
β
pH 7.50 pH 7.10
A C0 Cf
2
1
0
Cp J 0
100
200
300
400
500
600
Concentration (ppm)
Fig. 13. Effect of pH and initial concentration on separation factor with PES membranes (P ¼ 10 psi).
t TMP V1 , V2
effective membrane area (cm2) initial protein concentration (ppm) protein concentration in the feed (ppm) protein concentration in the permeate (ppm) permeate flux defined in Eq. (2) (cm3/(cm2 min)) filtration time (min) transmembrane pressure (psi) cumulative permeate volumes at time t1 and t2, respectively (cm3)
S.H. Lin et al. / Desalination 234 (2008) 116–125
Greek letters initial concentration ratio of Hb to BSA, i.e., (CHb,0/CBSA,0) separation factor defined in Eq. (3) (–)
[9]
[10] [11]
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Effect of operating parameters on the separation of proteins in aqueous solutions by dead-end ultrafiltration Su-Hsia Lina*, Chia-Lin Hungb, Ruey-Shin Juangb a
Department of Chemical Engineering, Nanya Institute of Technology, Chung-Li 320, Taiwan Fax þ886-3-4361070; email: [email protected] b Department of Chemical Engineering and Materials Science, Yuan Ze University, Chung-Li 32003, Taiwan Received 27 June 2007; accepted revised 21 September 2007
Abstract Ultrafiltration (UF) separation of hemoglobin (Hb, pI 7.1, MW 68,000) and bovine serum albumin (BSA, pI 4.7, MW 67,000) in aqueous solutions with PES (polyethersulfone, MWCO ¼ 100 kDa) and PAN (polyacrylonitrile, MWCO ¼ 100 kDa) membranes was studied. Experiments were performed by changing operating parameters including solution pH (4–7.5), initial protein concentration (100–500 ppm), transmembrane pressure (TMP, 10–50 psi), ionic strength (0.01–0.1 M), and stirring speed (100–300 rpm). More effective separation was achieved at a lower protein concentration, a lower TMP, or a pH above the pI of Hb with PAN membrane. Under the conditions of low pressure, low protein concentration, and low ionic strength, the interactions between the charges of proteins and membranes were important. The flux decreased more sharply when pH was lower than 7.1. Response surface methodology by the Box-Behnken model was used to examine the role of each process variable on protein rejection and UF flux. A second-order polynomial regression model could properly interpret the experimental data with an R2 value of 0.97, based on the estimated rejection of BSA up to 99.7%. Interactions between these operating parameters and the significance effects on UF operation were also discussed. Keywords: Separation; Proteins; Dead-end ultrafiltration; Operating parameters; Flux decline
1. Introduction The separation or purification of proteins is a crucial process in biotechnology due to its wide range of applications in biomedical and food
*Corresponding author.
industries. The techniques used for protein separation and purification such as chromatography, electrophoresis, and affinity operations have been recently established for producing small quantities of proteins in research laboratories. However, these techniques are rather difficult to scale-up, which limits production
Presented at the Fourth Conference of Aseanian Membrane Society (AMS 4), 16–18 August 2007, Taipei, Taiwan. 0011-9164/08/$– See front matter # 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.desal.2007.09.077
S.H. Lin et al. / Desalination 234 (2008) 116–125
levels [1–2]. Besides, some methods like chromatography and electrophoresis require complex instrumentation support to run efficiently, and usually yield low throughput of the products at an extremely high process cost. Hence, the separation techniques that can yield high throughput of the products at a low cost are highly desired in biotechnological industries. Of these potential candidates, ultrafiltration (UF) has attracted a considerable amount of attention in recent years for the separation of proteins due to comparatively gentler towards the proteins than separation process on phase changes and more economical than gel chromatography [3–8]. The applications of UF are limited to systems where the solutes to be separated have more than 10-fold difference in molecular weight (MW). Molecular size becomes the sole criteria for separation purposes in such cases. However, it is possible to separate solutes having comparable MWs by adequately manipulating the parameters such as pH, ionic strength, and transmembrane pressure (TMP) [3]. van Eijndhoven et al. [4] have shown the possibility to improve the selectivity of albumin (BSA)/hemoglobin (Hb) by reducing salt concentration and adjusting the pH to near isoelectric point (pI) of Hb. Feins and Sirkar [5] have separated binary proteins with relatively close in MW using internally staged UF. The fractionation of lysozyme (Ly)/ovalbumin and Ly/myoglobin mixtures by 100-kDa hydrophilic polyacrylonitrile membrane has been studied in a vortex flow ultrafilter [9]. Saksena and Zydney [3] have also studied the transport of IgG and BSA using 100- and 300-kDa PS membranes in a stirred cell. The separation of Ly and BSA by Amicon PM 30 membrane and the effect of salt concentration and BSA-Ly interaction on the rate of Ly washout were also examined [10]. However, the main problem restricting practical applications is membrane fouling and the resulting time-dependent flux and rejection behavior. The main factors that affect membrane fouling
117
are the physicochemical properties of feed and membrane [9]. This study will focus on these two factors. In this work, Hb and BSA were chosen as model proteins and the membranes with a molecular-weight cut-off (MWCO) of 100 kDa were selected. The effects of ionic strength, stirring speed, solution pH, and membrane hydrophobility were investigated in order to improve the separation and the performance of UF process. Response surface methodology by the Box-Behnken model was used to examine the role of each process variable on protein rejection and UF flux. A second-order polynomial regression model could use to predict the experimental data. Interactions between these process parameters and the significance effects on UF operation were also discussed. 2. Response surface methodology In the factorial design of experiments, when responses and input variable factors (e.g., the initial protein concentration, TMP, stirred speed, and solution pH) are continuous, it is very useful to consider the factor response relationship in terms of a mathematical model such as the response function. For qualitative factors where there is no continuous link between the response and the levels of a factor, it is necessary to consider a comparison of the response between two levels of a qualitative factor. The factorial approach results in a considerable saving of time and materials devoted to the experiments. First, the factor that is independent of all simple effects of a factor is equal to its main effect. The consequences of variations in the factors and the main effects are the only quantities that need to be stated. Second, each main effect in factorial experiments is estimated with the same accuracy as if the whole experiment had been devoted to the factor alone [11]. Thus, the advantages of this methodology contain (i) all experimental units are used in evaluating effects, resulting
S.H. Lin et al. / Desalination 234 (2008) 116–125
in the most efficient use of resources, (ii) the effects are evaluated over a wider range of conditions with the minimum of resources, and (iii) a factorial set of treatments is optimized for estimating main effects and interactions. In this work, the factorial design experiments are used in the analysis of protein rejection. Four input variables, protein concentration, TMP, stirred speed and solution pH, are considered. The use of variance analysis and factorial design of experiments allows us to express the rejection of protein as a polynomial model. If the levels of the factors are equally spaced, the orthogonal polynomial adopted to give a more detailed equation for the response will be [12] Y ¼ b0 þ b1 C þ b2 R þ b3 H þ b4 P þ b11 C 2 þ b22 R2 þ b33 H 2 þ b44 P2 þ b12 CR þ b13 CH þ b14 CP þ b23 RH þ b24 RP þ b34 HP
ð1Þ
where Y is the predicted response (rejection of protein), bi’s are the coefficients of the polynomial equation, C is the initial protein concentration (ppm), R is the stirring speed (rpm), H is the solution pH, and P is the TMP (psi). The method used for evaluating the effects and their sums squares is a simple extension of the method introduced by Yates for a 200 factorial design [11]. It is assumed that the main and interaction effects are all linear combinations of the observations. This design is preferred because relatively few combinations of the variables are adequate to estimate potentially complex response function. The total 29 experiments are needed to calculate 15 coefficients of the second-order polynomial regression model. This model contains 1 block term, 4 linear terms, 4 quadratic terms, and 6 interaction terms. A convenient way of estimating these effects for a factorial design is to establish a table of appropriate multipliers that applied to the observations.
3. Experimental 3.1. Reagents and membranes Hemoglobin (Hb, MW 68,000) and bovine serum albumin (BSA, MW 66,430) were offered from Sigma Co. The pI values for Hb and BSA are 7.1 and 4.9, respectively. The zeta potential of proteins was shown in Fig. 1. The single protein solution was prepared by dissolving protein in 50 mM phosphate buffer, in which the solution pH was controlled in the range 4.0–7.5. The solution was gently agitated for 1 h to ensure homogeneity at 25 C. Prior to use, the phosphate buffer was filtered through a 0.45-mm Durapore membrane (Millipore, Bedford, MA). The binary protein solution was obtained by mixing single stock solutions with gentle agitation for 20 min, and the solution was also pre-filtered through a 0.45-mm Durapore membrane to remove undissolved proteins and large particulates. The ionic strength of protein solutions was adjusted by the addition of NaCl. Polyestersulfone (PES) and polyacrylonitrile (PAN) disc membranes used were supplied from Osmonics Co. Both asymmetric membranes had a molecular-weight cut-off (MWCO) of 100 kDa. Prior to use, these membranes were 60 40
Zeta potential (mV)
118
BSA HB
20 0 –20 –40 –60
2
3
4
5
6
7
8
9
10
pH
Fig. 1. Zeta potentials of BSA and HB proteins at various pH values.
S.H. Lin et al. / Desalination 234 (2008) 116–125
The average permeate flux (J) at each run was calculated in the time intervals t1 and t2 by
–10 –12
Zeta potential (mV)
119
–14
J¼
–16
ð V2 V1 Þ Aðt2 t1 Þ
ð2Þ
–18 –20 PES membrane PAN membrane
–24 –22
3
4
5
6
7
8
9
10
where A is the effective membrane area cm2) and V is the volume of the permeate (cm3). Also, the average rejection of each protein (R) was obtained as follows:
pH
Fig. 2. Zeta potentials of PES and PAN membrane at various pH values.
soaked overnight in protein solutions to ensure the attainment of equilibrium between the membrane and protein molecules. Fig. 2 shows the zeta potentials of fresh membranes. The method was described in our previous study [13]. They are negatively charged under the pH range studied.
3.2. Dead-end UF experiments Batch UF experiments were performed in a stirred glass cell of 8.0 cm I.D. and 8 cm height (Amicon Model 8400). It had an effective membrane area of 41.8 cm2 and a cell volume of 400 cm3. The applied pressure of stirred cell was controlled by nitrogen gas. The feed (working) volume of solution was 250 cm3 and the stirring speed was in the range 100–300 rpm. The highest speed of 300 rpm was selected because it could provide effective agitation but prevent the formation of a series vortex in the cell. Experiments were carried out at 25 C. The solution pH was measured using a pH meter (Horiba F-23, Japan). Except in continuous experiments, the permeate was collected in every increment of 20 cm3.
R¼1
Cp Cf
ð3Þ
where Cp and Cf are the protein concentrations in the permeate and feed, respectively. The concentrations of binary proteins in the samples were determined using HPLC (Hitachi L-7100) on a Hypersil WP300 column (particle size 5 mm). Two mixtures of 0.1 vol.% trifluoroacetic acid in water and 0.1 vol.% trifluoroacetic acid in propanol were used as the mobile-phase gradient. The flow rate was 1 cm3/min. An aliquot of 10 mL of the sample was injected and analyzed with an UV detector (L-7420) at a wavelength of 280 nm. Each experiment was at least duplicated under identical conditions. The reproducibility of the measurements was within 7% (mostly, 5%).
3.3. Cleaning operations After the completion of each experiment, the membrane used was cleaned in ultrasonic cleaner with 0.1 M NaOH for approximately 30 min once and then with deionized water twice. The pure water flux was then re-checked. The integrity and performance of the membrane was considered to be maintained if pure water flux was within 95% of the virgin membrane. The cleaned membranes were stored in 0.05% sodium azide solution at 4 C.
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4. Result and discussions 4.1. Effects of TMP, initial concentration, and pH on the rejection of BSA Three levels of the initial protein concentration, solution pH, stirring speed, and TMP are selected for factorial design of experiments according to the method by Yates [11]. A total of 29 experiments were used for error estimation of the four-factorial linear and quadratic interactions. The main and interaction effects obtained are multiplied by appropriate coefficients and predicted data as shown in Table 1. Figs. 3–5 show the effects of TMP, initial protein concentration, and pH on the rejection of BSA with PAN membranes. It is found that the rejection of single protein (BSA) increases with increasing TMP and initial concentration (Fig. 1). At low TMP (10 psi), a maximum rejection of BSA is found at low pH, particular lower than pI value of the protein (4.9). This is because the positively charged protein would adsorb onto the negatively charged membrane at pH < 4.9. The result is consistent with previous reports
Fig. 3. Protein rejection on 3-D graphics for response surface optimization vs. concentration and applied pressure.
that the transmission of protein (BSA) decreases with increasing pH [14]. However, the influence of pH is negligible at high TMP and high initial concentration. In general, the linear terms are more significant than the quadratic interactions. It is shown
Table 1 Coefficients of the model [Eq. (1)] for rejection of BSA using the 100 kDa-PAN Coefficient
Value
Standard error
t for H0: coeff. ¼ 0
Prob > |t|
b0 b1 b2 b3 b4 b11 b22 b33 b44 b12 b13 b14 b23 b24 b34
1.605 1.37 –0.17 –1.31 2.04 –0.64 –0.52 0.96 –1.68 0.27 0.013 –0.14 –0.11 0.36 0.86
0.2362 0.1525 0.1525 0.1525 0.1525 0.2074 0.2074 0.2074 0.2074 0.2641 0.2641 0.2641 0.2641 0.2641 0.2641
– 8.98 –1.085 –8.573 13.37 –3.081 –2.4956 4.6088 –8.097 1.0235 0.049 –0.5356 –0.42178 1.3518 3.258
– <0.0001 0.2962 <0.0001 <0.0001 0.0081 0.0257 0.0004 <0.0001 0.3234 0.9613 0.6006 0.6796 0.1979 0.0057
S.H. Lin et al. / Desalination 234 (2008) 116–125
121
1.4
Flux (cm3/cm2 s)
1.2
pH 7.65 pH 7.10 pH 6.00 H2O
1.0
C0 = 100 ppm 300 rpm
0.8 0.6 0.4 0.2 0.0
0
10
20
30
40
50
60
ΔP (psi)
Fig. 4. Protein rejection on 3-D graphics for response surface optimization vs. solution pH and applied pressure.
that TMP and initial protein concentration are the most significant factors, and stirring speed is the less significant one in the present filtration process. This confirms the experimental observations as indicated above. It is noticed that the model parameters are determined by an ANOVA fitting exercise, so that the model could adequately describe most of the data. The model can then be used to ‘‘predict’’ the remaining data, e.g., the measurement made at 0.1 psi.
Fig. 6. Effect of pH and P on UF flux with PAN membranes (C0,BSA ¼ 100 ppm).
In other words, this model is essential predictive, rather than corrective.
4.2. Effects of pH and TMP on the flux of protein solutions Figs. 6 and 7 illustrate the effect of pH and TMP on the flux of binary proteins solution with PAN membranes. It is observed that the flux increases sharply with TMP and then levels off, particularly at lower initial protein concentrations (Fig. 6). Also, the effect of solution pH is 1.4 C0 = 500 ppm 300 rpm PAN pH 7.65 pH 7.10 pH 6.00 H2O
Flux (cm3/cm2 s)
1.2 1.0 0.8 0.6 0.4 0.2 0.0
0
10
20
30
40
50
60
ΔP (psi)
Fig. 5. Protein rejection on 3-D graphics for response surface optimization vs. concentration and solution pH.
Fig. 7. Effect of pH and P on UF flux with PAN membranes (C0,BSA ¼ 500 ppm).
S.H. Lin et al. / Desalination 234 (2008) 116–125
more important at low protein concentrations. At pH 6, the positively charged Hb would adsorb easily on the negatively charged membrane, and block the pores of the membrane. However, the repulsive force between the negatively charged proteins and membrane reduce the fouling at pH > 7.1. At higher protein concentration and TMP (Fig. 7), the effect of pH on the flux can be neglected. In such situations, the concentration polarization is more important, which is also indicated by the results of Design Expert mentioned above.
Figs. 8 and 9 show the effects of solution pH and TMP on the separation factor ( ), which is defined as ð1 RBSA Þ ð1 RHb Þ
ð4Þ
As shown in Fig. 8, the higher separation factor is obtained at lower TMP and at pH near the pI of Hb. This is because neutral Hb molecules (at pH 7.1) are easily aggregated themselves and not absorbed on the surface of the membrane by electrostatic attraction, resulting 4
β
3
pH 7.50 pH 7.10 pH 6.00
2
1
0
0
10
20
30
40
3
C BSA,0 = C Hb,0 = 500 ppm pH 7.50 pH 7.10 pH 6.00
2
1
0
0
10
20
30
40
50
60
ΔP (psi)
Fig. 9. Effect of pH and P on separation factor with PAN membranes (C0,BSA ¼ 500 ppm).
4.3. Effects of pH and TMP on the separation factor
¼
4
β
122
50
60
ΔP (psi)
Fig. 8. Effect of pH and P on separation factor with PAN membranes (C0,BSA ¼ 100 ppm).
in less fouling, but BSA can pass easily through the pores of the membrane. In contrast to pH 6.0, the serious fouling at pH 7.1 is found (Figs. 6 and 7). The positively charged Hb is preferentially absorbed on the surface of negatively charged membrane, so the separation of two proteins is difficult at pH 6.0. At pH 7.5, the separation factor is smaller than 1 (Fig. 8), which means that the amount of Hb passing through the membrane is more than that of BSA (that is, RHb < RBSA). This is a result of the greater repulsive force between BSA molecules and the membrane, compared to that between Hb molecules and the membrane. Some inconsistent results with earlier studies are actually observed. Watanabe et al. [15] have reported that relatively high levels of denaturation and consequently aggregation are found in acidic solution with pH below the pI of BSA. At such low pH, the forces between protein layers and polymeric films would increase. It was also shown that below isoelectric point the tertiary structure of proteins was disturbed upon interaction with the polymeric films [16]. At high feed concentration of 500 ppm, however, the electrostatic force can be ignored, and the serious fouling makes the separation factor close to 1 as shown in Fig. 9.
S.H. Lin et al. / Desalination 234 (2008) 116–125
4.4. Effects of protein concentration and ionic strength on the separation factor
0.5
10 C 0 (ppm) BSA:HB = 300:100 BSA:HB = 100:300 BSA:HB = 100:500 BSA:HB = 500:100
ΔP = 10 psi 300 rpm PAN
β
6
0.01 M 0.05 M 0.1 M
0.4
CBSA = CHB = 100 ppm ΔP = 10 psi 300 rpm PAN
0.3
β
At a concentration ratio (¼CHb,0/CBSA,0) of 1/3 or 1/5 (Fig. 10), BSA is likely the major protein deposited on the membrane. The dense deposition would retain both proteins passing through the membrane. However, at low values of 3 and 5, the separation factor closes 1 under the pH ranges studied. The neutral Hb is transported easier through the pores of the membrane by pressure driving force at pH 7.1, which leads to a low . But the separation factor is lower than 1 at pH > 7.1. The effect of ionic strength on the value is shown in Fig. 11. All the separation factor is smaller than 1, which decreases with increasing ionic strength at pH > 7.1. The addition of NaCl would offset the effect of electrostatic interactions, and decrease the thickness of double layer. The molecular size of Hb is seriously reduced, and it will pass through the membrane, resulting in a low of 0.025 at an ionic strength of 0.01 M and pH 7.5. This represents that another high separation factor (1/ ) is obtained. Although the molecular weight of Hb is higher that of BSA, the elliptical shape of Hb would pass easily through the pores of the membrane (equivalent
8
123
0.2
0.1
0.0 6.4
6.6
6.8
7.0
7.2
7.4
7.6
pH
Fig. 11. Effect of pH and ionic strength on separation factor with PAN membranes (C0,BSA ¼ 500 ppm).
radium in nm, BSA: 14 4 4, Hb: 7 5.5 5.5; and ellipsoidal diameter in nm: BSA: 3.61, Hb: 3.1 [17]). van Eijndhoven et al. [4] have ever investigated the selective separation of Hb and BSA with 100-kDa PES membrane in a stirred UF cell. They pointed out that a very high selectivity (1/ ¼ 70) is obtained for the separation of BAS and Hb at pH 7 and 0.0023 M NaCl. At the same ionic strength of 0.01 M, a higher separation factor with 100-kDa PAN membrane (1/ ¼ 40) is obtained here compared to that with 100-kDa PES membrane (1/ ¼ 5) in their experiments [4]. Causserand et al. [17] have also examined the separation of BSA and Hb by the addition of montmorillonite to enhance the selectivity with 0.1 mm PVDF membrane. However, the value increased from 1.61 to 5.63 only by adding 1.0 g/L at pH 7 and an ionic strength of 1 mM.
4 2
4.5. Effect of membrane materials on the flux and separation factor
0 6.4
6.6
6.8
7.0
7.2
7.4
7.6
pH
Fig. 10. Effect of pH and ionic strength on separation factor with PAN membranes (C0,BSA ¼ 500 ppm).
The effect of membrane materials on the flux is shown in Fig. 12. The lower flux is obtained with more hydrophobic membranes (PES). This is because that protein would adsorb easily on the
124
S.H. Lin et al. / Desalination 234 (2008) 116–125
1.2
pH 7.50, 100 ppm pH 7.10, 100 ppm pH 6.00, 100 ppm pH 7.50, 500 ppm pH 7.10, 500 ppm
(a)
1.0
J/J 0
0.8 PAN: 100 kDa Pressure: 10 psi Stirred rate: 300 rpm
0.6 0.4
PAN membrane is higher than that with PES membrane. It should be noted that a separation factor of 0.02 is obtained with PES membrane at pH 7.5 and an initial protein concentration of 100 ppm.
0.2 0.0
0
100
200
300
400
500
600
5. Conclusions
1.2 (b) 1.0
PES: 100 kDa pH: 7.50 Pressure: 10 psi Stirred rate: 300 rpm
J/J 0
0.8 0.6
CHb = CBSA 100 ppm 300 ppm 500 ppm
0.4 0.2 0.0
0
100
200
300
400
500
600
Time (s)
Fig. 12. Comparison of flux with PAN and PES (P ¼ 10 psi).
more hydrophobic membrane. These findings are similar to those reported by Musale and Kulkarni [18]. The separation factor at different solution pH with PES membrane is shown in Fig. 13. Comparing two kinds of membrane materials at an initial concentration of each protein of 100 ppm, we find that the separation factor with
The effects of operating parameters on the flux and separation factor in dead-end UF of binary BSA and Hb (with similar molecular weights) using PES and PAN membranes (MWCO, 100 kDa) were systematically investigated. The following results were obtained. (1) The UF flux and protein rejection were strongly affected by the applied pressure, solution pH and ionic strength, particularly mainly by the applied pressure and feed concentration. (2) The high separation of BSA and Hb can be obtained at the condition of lower applied pressure, low ionic strength and solution pH > pI of Hb. (3) Under comparable conditions, PAN membrane displayed higher UF flux and higher separation factor than that of PES membrane.
4 PES: 100 kDa ΔP : 10 psi Stirred rate: 300 rpm
3
Nomenclature
β
pH 7.50 pH 7.10
A C0 Cf
2
1
0
Cp J 0
100
200
300
400
500
600
Concentration (ppm)
Fig. 13. Effect of pH and initial concentration on separation factor with PES membranes (P ¼ 10 psi).
t TMP V1 , V2
effective membrane area (cm2) initial protein concentration (ppm) protein concentration in the feed (ppm) protein concentration in the permeate (ppm) permeate flux defined in Eq. (2) (cm3/(cm2 min)) filtration time (min) transmembrane pressure (psi) cumulative permeate volumes at time t1 and t2, respectively (cm3)
S.H. Lin et al. / Desalination 234 (2008) 116–125
Greek letters initial concentration ratio of Hb to BSA, i.e., (CHb,0/CBSA,0) separation factor defined in Eq. (3) (–)
[9]
[10] [11]
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